A big part of AI and Deep Learning these days is the tuning/optimizing of the algorithms for speed and accuracy. Much of today’s deep learning algorithms involve the use of the gradient descent ...

Abstract: Adam and RMSProp are two of the most influential adaptive stochastic algorithms for training deep neural networks, which have been pointed out to be divergent even in the convex setting via ...

To explore how different optimization algorithms perform under various conditions, such as polynomial degrees and training set sizes in linear regression. To evaluate how the optimizers behave when ...

Abstract: This paper proposes an intelligent joint control model of tobacco silk moisture based on deep learning algorithm to realize the intelligent linkage control of moisture regain, feeding and ...